package com.atguigu.gmall.realtime.app.dwd.db;

import com.atguigu.gmall.realtime.utils.MyKafkaUtil;
import com.atguigu.gmall.realtime.utils.MySqlUtil;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.table.api.Table;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;

/**
 * @author Felix
 * @date 2022/12/12
 * 交易域加购事实表
 * 需要启动的进程
 * zk、kafka、maxwell、DwdTradeCartAdd
 */
public class DwdTradeCartAdd {
    public static void main(String[] args) {
        //TODO 1.基本环境准备
        //1.1 指定流处理环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        //1.2 设置并行度
        env.setParallelism(4);
        //1.3 指定表执行环境
        StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env);

        /*//TODO 2.检查点相关设置
        //2.1 开启检查点
        env.enableCheckpointing(5000L, CheckpointingMode.EXACTLY_ONCE);
        //2.2 设置检查点超时时间
        env.getCheckpointConfig().setCheckpointTimeout(60000L);
        //2.3 设置job取消后检查点是否保留
        env.getCheckpointConfig().enableExternalizedCheckpoints(CheckpointConfig.ExternalizedCheckpointCleanup.RETAIN_ON_CANCELLATION);
        //2.4 设置两个检查点之间最小时间间隔
        env.getCheckpointConfig().setMinPauseBetweenCheckpoints(2000L);
        //2.5 设置重启策略
        env.setRestartStrategy(RestartStrategies.failureRateRestart(3, Time.days(30),Time.seconds(3)));
        //2.6 设置状态后端
        env.setStateBackend(new HashMapStateBackend());
        env.getCheckpointConfig().setCheckpointStorage("hdfs://hadoop202:8020/gmall/ck");
        //2.7 设置操作hadoop的用户
        System.setProperty("HADOOP_USER_NAME","atguigu");*/

        //TODO 3.从kafka的topic_db主题中读取数据，创建动态表
        tableEnv.executeSql(MyKafkaUtil.getTopicDbDDL("dwd_trade_cart_add_group"));
        // tableEnv.executeSql("select * from topic_db").print();

        //TODO 4.过滤出加购行为 ~~~ 加购表
        Table cartAdd = tableEnv.sqlQuery("select\n" +
            "    `data`['id'] id,\n" +
            "    `data`['user_id'] user_id,\n" +
            "    `data`['sku_id'] sku_id,\n" +
            "    if(`type`='insert',`data`['sku_num'],\n" +
            "    cast((CAST(`data`['sku_num'] AS INT) -  CAST(`old`['sku_num']AS INT)) as string)) sku_num,\n" +
            "    `data`['source_type'] source_type,\n" +
            "    ts,\n" +
            "    proc_time\n" +
            "from topic_db where `table`='cart_info' \n" +
            "and (`type` = 'insert' or (`type`='update' and `old`['sku_num'] is not null \n" +
            " and  CAST(`data`['sku_num'] AS INT) > CAST(`old`['sku_num']AS INT)))");
        tableEnv.createTemporaryView("cart_add", cartAdd);
        // tableEnv.executeSql("select * from cart_add").print();

        //TODO 5.从MySQL中读取字典数据 ~~~ 字典表
        tableEnv.executeSql(MySqlUtil.getBaseDicLookUpDDL());

        //TODO 6.关联加购表和字典表 ~~~ lookupJoin
        Table joinedTable = tableEnv.sqlQuery("SELECT \n" +
            "    cadd.id,\n" +
            "    cadd.user_id,\n" +
            "    cadd.sku_id,\n" +
            "    cadd.sku_num,\n" +
            "    cadd.ts,\n" +
            "    cadd.source_type,\n" +
            "    dic.dic_name source_type_name\n" +
            "FROM cart_add AS cadd JOIN base_dic FOR SYSTEM_TIME AS OF cadd.proc_time AS dic \n" +
            "ON cadd.source_type = dic.dic_code");
        tableEnv.createTemporaryView("joined_table", joinedTable);
        // tableEnv.executeSql("select * from joined_table").print();

        //TODO 7.将关联维度结果写到kafka主题中
        //7.1 创建动态表和要写入的kafka主题进行映射
        tableEnv.executeSql("CREATE TABLE dwd_trade_cart_add (\n" +
            "  id string,\n" +
            "  user_id string,\n" +
            "  sku_id string,\n" +
            "  sku_num string,\n" +
            "  ts string,\n" +
            "  source_type string,\n" +
            "  source_type_name string,\n" +
            "  PRIMARY KEY (id) NOT ENFORCED\n" +
            ")" + MyKafkaUtil.getUpsertKafkaDDL("dwd_trade_cart_add"));
        //7.2 写入
        tableEnv.executeSql("insert into dwd_trade_cart_add select * from joined_table");
    }


}
